# Analysis ID : Project XYZ Population PK Analysis
# Purpose : Summarize Base PK model
# Other Info : Define your own!
pkdata <- read.csv("pkdata.csv")
The purpose of this data memo is to provide a summary of the base population pharmacokinetic model fit for study XYZ, and to summarize simulated exposure target attainment as measured by Cmax and AUC24 following the first administered dose of study drug.
catcovsumm <- readRDS(file='catcovsumm.RDS')
catcovsumm
| Variable | Center | ||
|---|---|---|---|
| AB123456, N = 121 | AB567765, N = 501 | AB765432, N = 381 | |
| SEX | |||
| Male | 7 (58%) | 22 (44%) | 17 (45%) |
| Female | 5 (42%) | 28 (56%) | 21 (55%) |
| STATUS | |||
| HEALTHY | 7 (58%) | 10 (20%) | 13 (34%) |
| INFECTED | 5 (42%) | 40 (80%) | 25 (66%) |
| SETTING | |||
| Clinic | 0 (0%) | 50 (100%) | 0 (0%) |
| Inpatient | 12 (100%) | 0 (0%) | 38 (100%) |
|
1
n (%)
|
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contcovsumm <- readRDS(file='contcovsumm.RDS')
contcovsumm
| Variable | Center | ||
|---|---|---|---|
| AB123456, N = 121 | AB567765, N = 501 | AB765432, N = 381 | |
| WT | 74 (28) [44-126] | 69 (26) [34-121] | 74 (28) [34-153] |
| AGE | 58 (25) [31-93] | 57 (18) [27-90] | 49 (13) [27-90] |
| CRCL | 91 (10) [78-112] | 88 (11) [66-112] | 91 (11) [71-114] |
|
1
Mean (SD) [Minimum-Maximum]
|
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meanlinplot <- readRDS(file='meanlinplot.RDS')
meanlinplot
meanlogplot <- readRDS(file='meanlogplot.RDS')
meanlogplot
meanlinplotbysex <- readRDS(file='meanlinplotbysex.RDS')
meanlinplotbysex
meanlinplotbywt <- readRDS(file='meanlinplotbywt.RDS')
meanlinplotbywt
Structural PK Model
## View the updated model
model<-readRDS("model.RDS")
print(model)
## Loading required package: Certara.RsNLME
##
## Model Overview
## -------------------------------------------
## Is population : TRUE
## Model Type : PK
##
## PK
## -------------------------------------------
## Parameterization : Clearance
## Absorption : Intravenous
## Num Compartments : 2
## Dose Tlag? : FALSE
## Elimination Comp ?: FALSE
## Infusion Allowed ?: FALSE
## Sequential : FALSE
## Freeze PK : FALSE
##
## PML
## -------------------------------------------
## test(){
## cfMicro(A1,Cl/V, Cl2/V, Cl2/V2)
## dosepoint(A1)
## C = A1 / V
## error(CEps=0.2)
## observe(CObs=C * ( 1 + CEps))
## stparm(V = tvV * ((WT/70)^dVdWT) * exp(nV))
## stparm(Cl = tvCl * ((WT/70)^dCldWT) * exp(nCl))
## stparm(V2 = tvV2)
## stparm(Cl2 = tvCl2)
## fcovariate(WT)
## fcovariate(AGE)
## fcovariate(CRCL)
## fcovariate(SEX())
## fixef( tvV = c(,80,))
## fixef( tvCl = c(,6,))
## fixef( tvV2 = c(,100,))
## fixef( tvCl2 = c(,9,))
## fixef( dVdWT(enable=c(0)) = c(,0,))
## fixef( dCldWT(enable=c(1)) = c(,0,))
## ranef(diag(nV,nCl) = c(0.1,0.1))
## }
##
## Structural Parameters
## -------------------------------------------
## V Cl V2 Cl2
## -------------------------------------------
## Observations:
## Observation Name : CObs
## Effect Name : C
## Epsilon Name : CEps
## Epsilon Type : Multiplicative
## Epsilon frozen : FALSE
## is BQL : FALSE
## -------------------------------------------
## Column Mappings
## -------------------------------------------
## Model Variable Name : Data Column name
## id : ID
## time : TIME
## A1 : AMT
## WT : WT
## AGE : AGE
## CRCL : CRCL
## SEX : SEX( male=0 female=1 )
## CObs : DV
dvpred <- readRDS("dvpred.RDS")
dvpred
dvipred <- readRDS("dvipred.RDS")
dvipred
cwresidv <- readRDS("cwresidv.RDS")
cwresidv
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
cwrespred <- readRDS("cwrespred.RDS")
cwrespred
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
etacovcont <- readRDS("etacovcont.RDS")
## Registered S3 method overwritten by 'GGally':
## method from
## +.gg ggplot2
etacovcont
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
etacovcat <- readRDS("etacovcat.RDS")
etacovcat
tableoverall <- readRDS("tableoverall.RDS")
tableoverall
RetCode | Condition | LL | -2LL | AIC | BIC | nParm | nObs | nSub |
1 | 210.44 | 1,115.44 | -2,230.88 | -2,212.88 | -2,167.85 | 9 | 1,100 | 100 |
Source: script.R | ||||||||
tabletheta <- readRDS("tabletheta.RDS")
tabletheta
Name | Label | Value | SE | RSE% | 2.5% CI | 97.5% CI |
THETA(1) | tvV | 94.39 | 2.16 | 2.29 | 90.15 | 98.63 |
THETA(2) | tvCl | 5.11 | 0.22 | 4.37 | 4.68 | 5.55 |
THETA(3) | tvV2 | 97.35 | 9.00 | 9.25 | 79.69 | 115.01 |
THETA(4) | tvCl2 | 7.58 | 0.22 | 2.95 | 7.14 | 8.01 |
THETA(5) | dVdWT | 0.77 | 0.06 | 7.95 | 0.65 | 0.90 |
THETA(6) | dCldWT | 0.87 | 0.07 | 8.07 | 0.73 | 1.01 |
Source: script.R | ||||||
tableomega <- readRDS("tableomega.RDS")
tableomega
Name | Label | Value | SE | RSE% | Fixed | Diagonal | 2.5% CI | 97.5% CI | Shrinkage% |
OMEGA(1,1) | nV | 0.055 | 0.009 | 15.881 | FALSE | TRUE | 0.038 | 0.073 | 4.109 |
OMEGA(2,2) | nCl | 0.041 | 0.008 | 20.711 | FALSE | TRUE | 0.024 | 0.058 | 6.912 |
Source: script.R | |||||||||
tablesigma <- readRDS("tablesigma.RDS")
tablesigma
Name | Label | Value | SE | RSE% | Fixed | 2.5% CI | 97.5% CI | Shrinkage% |
SIGMA(1,1) | CEps | 0.127 | 0.004 | 2.808 | FALSE | 0.120 | 0.134 | 8.372 |
Source: script.R | ||||||||
vpcPlot <- readRDS("vpcPlot.RDS")
vpcPlot
TAplot <- readRDS("TAplot.RDS")
TAplot
TAplotbyWT <- readRDS("TAplotbyWT.RDS")
TAplotbyWT
sessionInfo()
R version 4.1.1 (2021-08-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] Certara.RsNLME_1.1.0 flextable_0.6.8
loaded via a namespace (and not attached):
[1] sass_0.4.0 tidyr_1.2.0 jsonlite_1.7.3
[4] splines_4.1.1 bslib_0.3.1 shiny_1.7.1
[7] assertthat_0.2.1 highr_0.9 yaml_2.2.2
[10] gdtools_0.2.3 shinymaterial_1.2.0 pillar_1.7.0
[13] backports_1.4.1 lattice_0.20-44 glue_1.6.1
[16] uuid_0.1-4 digest_0.6.29 RColorBrewer_1.1-2
[19] promises_1.2.0.1 polyclip_1.10-0 checkmate_2.0.0
[22] colorspace_2.0-2 plyr_1.8.6 htmltools_0.5.2
[25] httpuv_1.6.5 Matrix_1.3-4 pkgconfig_2.0.3
[28] purrr_0.3.4 xtable_1.8-4 scales_1.1.1
[31] tweenr_1.0.2 later_1.3.0 officer_0.4.0
[34] ggforce_0.3.3 tibble_3.1.6 mgcv_1.8-36
[37] generics_0.1.2 farver_2.1.0 ggplot2_3.3.5
[40] ellipsis_0.3.2 gtsummary_1.5.0 shinyjs_2.1.0
[43] cli_3.1.1 magrittr_2.0.2 crayon_1.5.0
[46] mime_0.12 evaluate_0.14 GGally_2.1.2
[49] fansi_1.0.2 broom.helpers_1.5.0 nlme_3.1-152
[52] MASS_7.3-54 xml2_1.3.3 tools_4.1.1
[55] data.table_1.14.2 lifecycle_1.0.1 stringr_1.4.0
[58] munsell_0.5.0 zip_2.2.0 Certara.NLME8_1.2.0
[61] compiler_4.1.1 jquerylib_0.1.4 xpose_0.4.13
[64] systemfonts_1.0.2 rlang_1.0.0 grid_4.1.1
[67] gt_0.3.1 rstudioapi_0.13 base64enc_0.1-3
[70] labeling_0.4.2 rmarkdown_2.11 egg_0.4.5
[73] gtable_0.3.0 reshape_0.8.8 DBI_1.1.1
[76] R6_2.5.1 gridExtra_2.3 knitr_1.37
[79] dplyr_1.0.7 fastmap_1.1.0.9000 utf8_1.2.2
[82] commonmark_1.7 Certara.Xpose.NLME_1.1.0 stringi_1.7.6
[85] Rcpp_1.0.8 vctrs_0.3.8 tidyselect_1.1.1
[88] xfun_0.29